Data Science and generative-AI

H. Brydon${}^a$ and R. Luus${}^a$

${}^a$University of the Western Cape, South Africa

There are multiple definitions of Data Science but academically, we tend to view this definition as cross-disciplinary in that it is the culmination of knowledge and skills across the disciplines of Mathematics, Statistics and Computer Science. The arrival and development of generative-AI technologies within the last few years, challenges us to rethink some of the core pedagogies within this definition of Data Science.

This is not to say that the respective disciplines require change within this definition of Data Science but perhaps they do need a rethink in terms of how generative-AI would complement their usage in practise. The research presented here looks at an application and usage of generative-AI in the development and preparation of data for Statistical modelling.

The research presented will showcase how generative-AI can be used to efficiently develop code scripts for simulating data with a wide variety of characteristics. This development process further identified potential areas where critical thinking becomes even more pertinent than before and comments to this end will be included in the discussion.

Keywords: Data science, generative-AI, data simulation, critical thinking.